3 papers
cs.CL2025
SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution
Hanlin Wang, Chak Tou Leong, Jiashuo Wang +2
Reinforcement learning (RL) holds significant promise for training LLM agents to handle complex, goal-oriented tasks that require multi-step interactions with external environments…
cs.LG2025
STeCa: Step-level Trajectory Calibration for LLM Agent Learning
Hanlin Wang, Jian Wang, Chak Tou Leong +1
Large language model (LLM)-based agents have shown promise in tackling complex tasks by interacting dynamically with the environment. Existing work primarily focuses on behavior cl…
cs.CL2024
E2CL: Exploration-based Error Correction Learning for Embodied Agents
Hanlin Wang, Chak Tou Leong, Jian Wang +1
Language models are exhibiting increasing capability in knowledge utilization and reasoning. However, when applied as agents in embodied environments, they often suffer from misali…